{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/krasserm/bayesian-machine-learning/blob/master/bayesian_optimization.ipynb)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "try:\n",
    "    # Check if notebook is running in Google Colab\n",
    "    import google.colab\n",
    "    # Get additional files from Github\n",
    "    !wget https://raw.githubusercontent.com/krasserm/bayesian-machine-learning/master/bayesian_optimization_util.py\n",
    "    # Install additional dependencies\n",
    "    !pip install scikit-optimize==0.5.2\n",
    "    !pip install GPy==1.9.8\n",
    "    !pip install GPyOpt==1.2.1\n",
    "    !pip install xgboost==0.90\n",
    "except:\n",
    "    pass"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Bayesian optimization\n",
    "\n",
    "## Introduction \n",
    "\n",
    "Many optimization problems in machine learning are black box optimization problems where the objective function $f(\\mathbf{x})$ is a black box function<sup>[1][2]</sup>. We do not have an analytical expression for $f$ nor do we know its derivatives. Evaluation of the function is restricted to sampling at a point $\\mathbf{x}$ and getting a possibly noisy response. \n",
    "\n",
    "If $f$ is cheap to evaluate we could sample at many points e.g. via grid search, random search or numeric gradient estimation. However, if function evaluation is expensive e.g. tuning hyperparameters of  a deep neural network, probe drilling for oil at given geographic coordinates or evaluating the effectiveness of a drug candidate taken from a chemical search space then it is important to minimize the number of samples drawn from the black box function $f$.\n",
    "\n",
    "This is the domain where Bayesian optimization techniques are most useful. They attempt to find the global optimimum in a minimum number of steps. Bayesian optimization incorporates prior belief about $f$ and updates the prior with samples drawn from $f$ to get a posterior that better approximates $f$. The model used for approximating the objective function is called *surrogate model*. Bayesian optimization also uses an *acquisition function* that directs sampling to areas where an improvement over the current best observation is likely.\n",
    "\n",
    "### Surrogate model\n",
    "\n",
    "A popular surrogate model for Bayesian optimization are [Gaussian processes](https://en.wikipedia.org/wiki/Gaussian_process) (GPs). I wrote about Gaussian processes in a [previous post](https://krasserm.github.io/2018/03/19/gaussian-processes/). If you are not familiar with GPs I recommend reading it first. GPs define a prior over functions and we can use them to incorporate prior beliefs about the objective function (smoothness, ...). The GP posterior is cheap to evaluate and is used to propose points in the search space where sampling is likely to yield an improvement. \n",
    "\n",
    "### Acquisition functions\n",
    "\n",
    "Proposing sampling points in the search space is done by acquisition functions. They trade off exploitation and exploration. Exploitation means sampling where the surrogate model predicts a high objective and exploration means sampling at locations where the prediction uncertainty is high. Both correspond to high acquisition function values and the goal is to maximize the acquisition function to determine the next sampling point. \n",
    "\n",
    "\n",
    "\n",
    "More formally, the objective function $f$ will be sampled at $\\mathbf{x}_t = \\mathrm{argmax}_{\\mathbf{x}} u(\\mathbf{x} \\lvert \\mathcal{D}_{1:t-1})$ where $u$ is the acquisition function and $\\mathcal{D}_{1:t-1} = \\{(\\mathbf{x}_1, y_1),...,(\\mathbf{x}_{t-1}, y_{t-1})\\}$ are the $t-1$ samples drawn from $f$ so far. Popular acquisition functions are *maximum probability of improvement* (MPI), *expected improvement* (EI) and *upper confidence bound* (UCB)<sup>[1]</sup>. In the following, we will use the expected improvement (EI) which is most widely used and described further below. \n",
    "\n",
    "### Optimization algorithm\n",
    "\n",
    "The Bayesian optimization procedure is as follows. For $t = 1,2,...$ repeat:\n",
    "\n",
    "- Find the next sampling point $\\mathbf{x}_{t}$ by optimizing the acquisition function over the GP: $\\mathbf{x}_t = \\mathrm{argmax}_{\\mathbf{x}} u(\\mathbf{x} \\lvert \\mathcal{D}_{1:t-1})$\n",
    "- Obtain a possibly noisy sample $y_t = f(\\mathbf{x}_t) + \\epsilon_t$ from the objective function $f$.\n",
    "- Add the sample to previous samples $\\mathcal{D}_{1:t} = \\{\\mathcal{D}_{1:t-1}, (\\mathbf{x}_t,y_t)\\}$ and update the GP.\n",
    "\n",
    "### Expected improvement\n",
    "\n",
    "Expected improvement is defined as\n",
    "\n",
    "$$\\mathrm{EI}(\\mathbf{x}) = \\mathbb{E}\\max(f(\\mathbf{x}) - f(\\mathbf{x}^+), 0)\\tag{1}$$\n",
    "\n",
    "where $f(\\mathbf{x}^+)$ is the value of the best sample so far and $\\mathbf{x}^+$ is the location of that sample i.e. $\\mathbf{x}^+ = \\mathrm{argmax}_{\\mathbf{x}_i \\in \\mathbf{x}_{1:t}} f(\\mathbf{x}_i)$. The expected improvement can be evaluated analytically under the GP model<sup>[3]</sup>:\n",
    "\n",
    "$$\n",
    "\\mathrm{EI}(\\mathbf{x}) =\n",
    "\\begin{cases}\n",
    "(\\mu(\\mathbf{x}) - f(\\mathbf{x}^+) - \\xi)\\Phi(Z) + \\sigma(\\mathbf{x})\\phi(Z)  &\\text{if}\\ \\sigma(\\mathbf{x}) > 0 \\\\\n",
    "0 & \\text{if}\\ \\sigma(\\mathbf{x}) = 0\n",
    "\\end{cases}\\tag{2}\n",
    "$$\n",
    "\n",
    "where\n",
    "\n",
    "$$\n",
    "Z =\n",
    "\\begin{cases}\n",
    "\\frac{\\mu(\\mathbf{x}) - f(\\mathbf{x}^+) - \\xi}{\\sigma(\\mathbf{x})} &\\text{if}\\ \\sigma(\\mathbf{x}) > 0 \\\\\n",
    "0 & \\text{if}\\ \\sigma(\\mathbf{x}) = 0\n",
    "\\end{cases}\n",
    "$$\n",
    "\n",
    "where $\\mu(\\mathbf{x})$ and $\\sigma(\\mathbf{x})$ are the mean and the standard deviation of the GP pesterior predictive at $\\mathbf{x}$, respectively. $\\Phi$ and $\\phi$ are the CDF and PDF of the standard normal distribution, respectively. The first summation term in Equation (2) is the exploitation term and second summation term is the exploration term.\n",
    "\n",
    "Parameter $\\xi$ in Equation (2) determines the amount of exploration during optimization and higher $\\xi$ values lead to more exploration. In other words, with increasing $\\xi$ values, the importance of improvements predicted by the GP posterior mean $\\mu(\\mathbf{x})$ decreases relative to the importance of potential improvements in regions of high prediction uncertainty, represented by large $\\sigma(\\mathbf{x})$ values. A recommended default value for $\\xi$ is $0.01$.\n",
    "\n",
    "With this minimum of theory we can start implementing Bayesian optimization. The next section shows a basic implementation with plain NumPy and SciPy, later sections demonstrate how to use existing libraries. Finally, Bayesian optimization is used to tune the hyperparameters of a tree-based regression model."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Implementation with NumPy and SciPy\n",
    "\n",
    "In this section, we will implement the acquisition function and its optimization in plain NumPy and SciPy and use scikit-learn for the Gaussian process implementation. Although we have an analytical expression of the optimization objective `f` in the following example, we treat is as black box and iteratively approximate it with a Gaussian process during Bayesian optimization. Furthermore, samples drawn from the objective function are noisy and the noise level is given by the `noise` variable. Optimization is done within given `bounds`. We also assume that there exist two initial samples in `X_init` and `Y_init`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "bounds = np.array([[-1.0, 2.0]])\n",
    "noise = 0.2\n",
    "\n",
    "def f(X, noise=noise):\n",
    "    return -np.sin(3*X) - X**2 + 0.7*X + noise * np.random.randn(*X.shape)\n",
    "\n",
    "X_init = np.array([[-0.9], [1.1]])\n",
    "Y_init = f(X_init)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following plot shows the noise-free objective function, the amount of noise by plotting a large number of samples and the two initial samples."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Dense grid of points within bounds\n",
    "X = np.arange(bounds[:, 0], bounds[:, 1], 0.01).reshape(-1, 1)\n",
    "\n",
    "# Noise-free objective function values at X \n",
    "Y = f(X,0)\n",
    "\n",
    "# Plot optimization objective with noise level \n",
    "plt.plot(X, Y, 'y--', lw=2, label='Noise-free objective')\n",
    "plt.plot(X, f(X), 'bx', lw=1, alpha=0.1, label='Noisy samples')\n",
    "plt.plot(X_init, Y_init, 'kx', mew=3, label='Initial samples')\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Goal is to find the global optimum on the left in a small number of steps. The next step is to implement the acquisition function defined in Equation (2) as `expected_improvement` function. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.stats import norm\n",
    "\n",
    "def expected_improvement(X, X_sample, Y_sample, gpr, xi=0.01):\n",
    "    '''\n",
    "    Computes the EI at points X based on existing samples X_sample\n",
    "    and Y_sample using a Gaussian process surrogate model.\n",
    "    \n",
    "    Args:\n",
    "        X: Points at which EI shall be computed (m x d).\n",
    "        X_sample: Sample locations (n x d).\n",
    "        Y_sample: Sample values (n x 1).\n",
    "        gpr: A GaussianProcessRegressor fitted to samples.\n",
    "        xi: Exploitation-exploration trade-off parameter.\n",
    "    \n",
    "    Returns:\n",
    "        Expected improvements at points X.\n",
    "    '''\n",
    "    mu, sigma = gpr.predict(X, return_std=True)\n",
    "    mu_sample = gpr.predict(X_sample)\n",
    "\n",
    "    sigma = sigma.reshape(-1, 1)\n",
    "    \n",
    "    # Needed for noise-based model,\n",
    "    # otherwise use np.max(Y_sample).\n",
    "    # See also section 2.4 in [...]\n",
    "    mu_sample_opt = np.max(mu_sample)\n",
    "\n",
    "    with np.errstate(divide='warn'):\n",
    "        imp = mu - mu_sample_opt - xi\n",
    "        Z = imp / sigma\n",
    "        ei = imp * norm.cdf(Z) + sigma * norm.pdf(Z)\n",
    "        ei[sigma == 0.0] = 0.0\n",
    "\n",
    "    return ei"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We also need a function that proposes the next sampling point by computing the location of the acquisition function maximum. Optimization is restarted `n_restarts` times to avoid local optima."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.optimize import minimize\n",
    "\n",
    "def propose_location(acquisition, X_sample, Y_sample, gpr, bounds, n_restarts=25):\n",
    "    '''\n",
    "    Proposes the next sampling point by optimizing the acquisition function.\n",
    "    \n",
    "    Args:\n",
    "        acquisition: Acquisition function.\n",
    "        X_sample: Sample locations (n x d).\n",
    "        Y_sample: Sample values (n x 1).\n",
    "        gpr: A GaussianProcessRegressor fitted to samples.\n",
    "\n",
    "    Returns:\n",
    "        Location of the acquisition function maximum.\n",
    "    '''\n",
    "    dim = X_sample.shape[1]\n",
    "    min_val = 1\n",
    "    min_x = None\n",
    "    \n",
    "    def min_obj(X):\n",
    "        # Minimization objective is the negative acquisition function\n",
    "        return -acquisition(X.reshape(-1, dim), X_sample, Y_sample, gpr)\n",
    "    \n",
    "    # Find the best optimum by starting from n_restart different random points.\n",
    "    for x0 in np.random.uniform(bounds[:, 0], bounds[:, 1], size=(n_restarts, dim)):\n",
    "        res = minimize(min_obj, x0=x0, bounds=bounds, method='L-BFGS-B')        \n",
    "        if res.fun < min_val:\n",
    "            min_val = res.fun[0]\n",
    "            min_x = res.x           \n",
    "            \n",
    "    return min_x.reshape(-1, 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we have all components needed to run Bayesian optimization with the [algorithm](#Optimization-algorithm) outlined above. The Gaussian process in the following example is configured with a [Matérn kernel](http://scikit-learn.org/stable/modules/gaussian_process.html#matern-kernel) which is a generalization of the squared exponential kernel or RBF kernel. The known noise level is configured with the `alpha` parameter. \n",
    "\n",
    "Bayesian optimization runs for 10 iterations. In each iteration, a row with two plots is produced. The left plot shows the noise-free objective function, the surrogate function which is the GP posterior predictive mean, the 95% confidence interval of the mean and the noisy samples obtained from the objective function so far. The right plot shows the acquisition function. The vertical dashed line in both plots shows the proposed sampling point for the next iteration which corresponds to the maximum of the acquisition function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x2160 with 20 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.gaussian_process import GaussianProcessRegressor\n",
    "from sklearn.gaussian_process.kernels import ConstantKernel, Matern\n",
    "from bayesian_optimization_util import plot_approximation, plot_acquisition\n",
    "\n",
    "# Gaussian process with Matérn kernel as surrogate model\n",
    "m52 = ConstantKernel(1.0) * Matern(length_scale=1.0, nu=2.5)\n",
    "gpr = GaussianProcessRegressor(kernel=m52, alpha=noise**2)\n",
    "\n",
    "# Initialize samples\n",
    "X_sample = X_init\n",
    "Y_sample = Y_init\n",
    "\n",
    "# Number of iterations\n",
    "n_iter = 10\n",
    "\n",
    "plt.figure(figsize=(12, n_iter * 3))\n",
    "plt.subplots_adjust(hspace=0.4)\n",
    "\n",
    "for i in range(n_iter):\n",
    "    # Update Gaussian process with existing samples\n",
    "    gpr.fit(X_sample, Y_sample)\n",
    "\n",
    "    # Obtain next sampling point from the acquisition function (expected_improvement)\n",
    "    X_next = propose_location(expected_improvement, X_sample, Y_sample, gpr, bounds)\n",
    "    \n",
    "    # Obtain next noisy sample from the objective function\n",
    "    Y_next = f(X_next, noise)\n",
    "    \n",
    "    # Plot samples, surrogate function, noise-free objective and next sampling location\n",
    "    plt.subplot(n_iter, 2, 2 * i + 1)\n",
    "    plot_approximation(gpr, X, Y, X_sample, Y_sample, X_next, show_legend=i==0)\n",
    "    plt.title(f'Iteration {i+1}')\n",
    "\n",
    "    plt.subplot(n_iter, 2, 2 * i + 2)\n",
    "    plot_acquisition(X, expected_improvement(X, X_sample, Y_sample, gpr), X_next, show_legend=i==0)\n",
    "    \n",
    "    # Add sample to previous samples\n",
    "    X_sample = np.vstack((X_sample, X_next))\n",
    "    Y_sample = np.vstack((Y_sample, Y_next))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note how the two initial samples initially drive search into the direction of the local maximum on the right side but exploration allows the algorithm to escape from that local optimum and find the global optimum on the left side. Also note how sampling point proposals often fall within regions of high uncertainty (exploration) and are not only driven by the highest surrogate function values (exploitation).\n",
    "\n",
    "A convergence plot reveals how many iterations are needed the find a maximum and if the sampling point proposals stay around that maximum i.e. converge to small proposal differences between consecutive steps. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x216 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from bayesian_optimization_util import plot_convergence\n",
    "\n",
    "plot_convergence(X_sample, Y_sample)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Bayesian optimization libraries\n",
    "\n",
    "There are numerous Bayesian optimization libraries out there and giving a comprehensive overview is not the goal of this article. Instead, I'll pick two that I used in the past and show the minimum setup needed to get the previous example running.\n",
    "\n",
    "### Scikit-optimize\n",
    "\n",
    "[Scikit-optimize](https://scikit-optimize.github.io/) is a library for sequential model-based optimization that is based on [scikit-learn](http://scikit-learn.org/). It also supports Bayesian optimization using Gaussian processes. The API is designed around minimization, hence, we have to provide negative objective function values.  The results obtained here slightly differ from previous results because of non-deterministic optimization behavior and different noisy samples drawn from the objective function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10ab4a748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.base import clone\n",
    "from skopt import gp_minimize\n",
    "from skopt.learning import GaussianProcessRegressor\n",
    "from skopt.learning.gaussian_process.kernels import ConstantKernel, Matern\n",
    "\n",
    "# Use custom kernel and estimator to match previous example\n",
    "m52 = ConstantKernel(1.0) * Matern(length_scale=1.0, nu=2.5)\n",
    "gpr = GaussianProcessRegressor(kernel=m52, alpha=noise**2)\n",
    "\n",
    "r = gp_minimize(lambda x: -f(np.array(x))[0], \n",
    "                bounds.tolist(),\n",
    "                base_estimator=gpr,\n",
    "                acq_func='EI',      # expected improvement\n",
    "                xi=0.01,            # exploitation-exploration trade-off\n",
    "                n_calls=10,         # number of iterations\n",
    "                n_random_starts=0,  # initial samples are provided\n",
    "                x0=X_init.tolist(), # initial samples\n",
    "                y0=-Y_init.ravel())\n",
    "\n",
    "# Fit GP model to samples for plotting results\n",
    "gpr.fit(r.x_iters, -r.func_vals)\n",
    "\n",
    "# Plot the fitted model and the noisy samples\n",
    "plot_approximation(gpr, X, Y, r.x_iters, -r.func_vals, show_legend=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10f88d208>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_convergence(np.array(r.x_iters), -r.func_vals)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## GPyOpt\n",
    "\n",
    "[GPyOpt](http://sheffieldml.github.io/GPyOpt/) is a Bayesian optimization library based on [GPy](https://sheffieldml.github.io/GPy/). The abstraction level of the API is comparable to that of scikit-optimize. The `BayesianOptimization` API provides a `maximize` parameter to configure whether the objective function shall be maximized or minimized (default). In version 1.2.1, this seems to be ignored when providing initial samples, so we have to negate their target values manually in the following example. Also, the built-in `plot_acquisition` and `plot_convergence` methods display the minimization result in any case. Again, the results obtained here slightly differ from previous results because of non-deterministic optimization behavior and different noisy samples drawn from the objective function. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10f8d3518>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import GPy\n",
    "import GPyOpt\n",
    "\n",
    "from GPyOpt.methods import BayesianOptimization\n",
    "\n",
    "kernel = GPy.kern.Matern52(input_dim=1, variance=1.0, lengthscale=1.0)\n",
    "bds = [{'name': 'X', 'type': 'continuous', 'domain': bounds.ravel()}]\n",
    "\n",
    "optimizer = BayesianOptimization(f=f, \n",
    "                                 domain=bds,\n",
    "                                 model_type='GP',\n",
    "                                 kernel=kernel,\n",
    "                                 acquisition_type ='EI',\n",
    "                                 acquisition_jitter = 0.01,\n",
    "                                 X=X_init,\n",
    "                                 Y=-Y_init,\n",
    "                                 noise_var = noise**2,\n",
    "                                 exact_feval=False,\n",
    "                                 normalize_Y=False,\n",
    "                                 maximize=True)\n",
    "\n",
    "optimizer.run_optimization(max_iter=10)\n",
    "optimizer.plot_acquisition()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10f592128>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "optimizer.plot_convergence()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Application\n",
    "\n",
    "This section demonstrates how to optimize the hyperparameters of an `XGBRegressor` with GPyOpt and how Bayesian optimization performance compares to random search. `XGBRegressor` is part of [XGBoost](https://xgboost.readthedocs.io/), a flexible and scalable gradient boosting library. `XGBRegressor` implements the scikit-learn estimator API and can be applied to regression problems. Regression is performed on a small [toy dataset](http://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_diabetes.html#sklearn.datasets.load_diabetes) that is part of scikit-learn."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn import datasets\n",
    "from sklearn.model_selection import RandomizedSearchCV, cross_val_score\n",
    "\n",
    "from scipy.stats import uniform\n",
    "from xgboost import XGBRegressor\n",
    "\n",
    "# Load the diabetes dataset (for regression)\n",
    "X, Y = datasets.load_diabetes(return_X_y=True)\n",
    "\n",
    "# Instantiate an XGBRegressor with default hyperparameter settings\n",
    "xgb = XGBRegressor()\n",
    "\n",
    "# and compute a baseline to beat with hyperparameter optimization \n",
    "baseline = cross_val_score(xgb, X, Y, scoring='neg_mean_squared_error').mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Hyperparameter tuning with random search\n",
    "\n",
    "For hyperparameter tuning with random search, we use `RandomSearchCV` of scikit-learn and compute a cross-validation score for each randomly selected point in hyperparameter space. Results will be discussed below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Hyperparameters to tune and their ranges\n",
    "param_dist = {\"learning_rate\": uniform(0, 1),\n",
    "              \"gamma\": uniform(0, 5),\n",
    "              \"max_depth\": range(1,50),\n",
    "              \"n_estimators\": range(1,300),\n",
    "              \"min_child_weight\": range(1,10)}\n",
    "\n",
    "rs = RandomizedSearchCV(xgb, param_distributions=param_dist, \n",
    "                        scoring='neg_mean_squared_error', n_iter=25)\n",
    "\n",
    "# Run random search for 25 iterations\n",
    "rs.fit(X, Y);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Hyperparameter tuning with Bayesian optimization\n",
    "\n",
    "To tune hyperparameters with Bayesian optimization we implement an objective function `cv_score` that takes hyperparameters as input and returns a cross-validation score. Here, we assume that cross-validation at a given point in hyperparameter space is deterministic and therefore set the `exact_feval` parameter of `BayesianOptimization` to `True`. Depending on model fitting and cross-validation details this might not be the case but we ignore that here."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "bds = [{'name': 'learning_rate', 'type': 'continuous', 'domain': (0, 1)},\n",
    "        {'name': 'gamma', 'type': 'continuous', 'domain': (0, 5)},\n",
    "        {'name': 'max_depth', 'type': 'discrete', 'domain': (1, 50)},\n",
    "        {'name': 'n_estimators', 'type': 'discrete', 'domain': (1, 300)},\n",
    "        {'name': 'min_child_weight', 'type': 'discrete', 'domain': (1, 10)}]\n",
    "\n",
    "# Optimization objective \n",
    "def cv_score(parameters):\n",
    "    parameters = parameters[0]\n",
    "    score = cross_val_score(\n",
    "                XGBRegressor(learning_rate=parameters[0],\n",
    "                              gamma=int(parameters[1]),\n",
    "                              max_depth=int(parameters[2]),\n",
    "                              n_estimators=int(parameters[3]),\n",
    "                              min_child_weight = parameters[4]), \n",
    "                X, Y, scoring='neg_mean_squared_error').mean()\n",
    "    score = np.array(score)\n",
    "    return score\n",
    "\n",
    "optimizer = BayesianOptimization(f=cv_score, \n",
    "                                 domain=bds,\n",
    "                                 model_type='GP',\n",
    "                                 acquisition_type ='EI',\n",
    "                                 acquisition_jitter = 0.05,\n",
    "                                 exact_feval=True, \n",
    "                                 maximize=True)\n",
    "\n",
    "# Only 20 iterations because we have 5 initial random points\n",
    "optimizer.run_optimization(max_iter=20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Results\n",
    "\n",
    "On average, Bayesian optimization finds a better optimium in a smaller number of steps than random search and beats the baseline in almost every run. This trend becomes even more prominent in higher-dimensional search spaces. Here, the search space is 5-dimensional which is rather low to substantially profit from Bayesian optimization. One advantage of random search is that it is trivial to parallelize. Parallelization of Bayesian optimization is much harder and subject to research (see \\[4\\], for example)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Baseline neg. MSE = -3498.95\n",
      "Random search neg. MSE = -3678.77\n",
      "Bayesian optimization neg. MSE = -3185.50\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZcAAAEWCAYAAACqitpwAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4xLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvAOZPmwAAIABJREFUeJzt3Xl8VNXd+PHPl50gi4QoyJKgUqwsYYksLoiiqLU+WLfqg4qKUG2t2ipuWMWFp1htbX1cEKuCguJSUZ4WEfTnvgYQZBeEsET2fZfA9/fHuRNuwsxkkszMnUy+79frvmbuuffcOXcmme+cc+45V1QVY4wxJp5qBF0AY4wx6ceCizHGmLiz4GKMMSbuLLgYY4yJOwsuxhhj4s6CizHGmLiz4GLKJCI5IqIiUivJr1tfRP5PRLaJyBsx5vlIRK6P0+sXiMhZ8ThWVSMiY0Xk4WTnNenDgks1ICJTReTBMOkDRGRtsoNGOVwCHA1kquqlpTeKyAgRGZ/8YlVcVSxzvIlICxF5XkTWiMgOEVkkIg+ISAPv+XVh8twiIjOCKK+pGAsu1cM44EoRkVLpVwETVLUogDLFIhv4PoXLZ8pJRJoCXwL1gd6q2hA4G2gCHIf7W706TNarvG1JJY59T1aEqtqS5gvuH3kb0MeXdiSwF8j11s8HvgW2A6uAEb59cwAFannrBcBZvu0jgPG+9V7AF8BWYA7QN0rZfg585O07H/gvL/0B4CdgP7ATGFwq37mlts/x0j8CHgI+B3YA04BmFSxbAXA3sADYArwI1PNt/yUw2zvWF0Bn37Y7gUKvDIuBfpHKHOZ1D8vrpffAfTFvBdYATwJ1fPkU+C2wxMv7EO4L+wvvc309tD/QF1gN3ANs9M51oO9YY4GHYzzXrsAs7zVfAyb685Y6t4eBuUCNCNtbAUVAti/tRO99a1bO96umd34/eNtmAq29bScD+bj/i3zgZN/xPgJGen9De4DjgcbA8977XuidR82g/7dTeQm8ALYk6YOG54B/+tZ/A8z2rfcFOuFqs52BdcCF3rYcYgwuQEtgE/AL71hne+tZYcpUG1jqfQHUAc70vgTalz5uhHM6bLv3xfAD8DNcUP0IGFXesvnOcx7QGmjqfdk87G3rCqwHenpfYoO8/esC7XEB+hjf+3dcjOcULW93XHCs5aUvBG715VXgHaAR0AHYB3wAHOt9OS4ABvk+7yLgb16ZTwd2+d77sTGeax1gBfAH7/O8BBc8IwWXr4AHyvhbnQ7c61v/M/B2Bd6vYbhA1h4QIBfI9D7LLbjaUC3gCm890/c3tNJ7D2t55zUJeBZoABwFfAP8Juj/61RerLpXfYwDLhGRet761fiaGVT1I1Wdq6oHVfU74FXcF055XQlMUdUp3rGmAzNwX+il9QKOwH35/6Sq/w/4N+6fvTJeVNXvVXUP7td6lwqULeRJVV2lqptxv2ZDZRsKPKuqX6vqAVUdh/sy7wUcwH3xnigitVW1QFV/iLHsEfOq6kxV/UpVi1S1APdlV/oz+ouqblfV+bjAOE1Vl6nqNuBdXKDw+5Oq7lPVj4H/AJeFKVO0c+2F+/L9u6ruV9U3cTWBSDJxv/6jGYf74sdrkhpI5CaxaO/19bggtVidOaq6CVdLX6KqL3vv5avAIuAC33HHqup8dU2yTXF/I7eq6i5VXQ88DlxexnlUaxZcqglV/QzX/HGhiByHa2J5JbRdRHqKyIciskFEtgE3AM0q8FLZwKUisjW0AKcCLcLsewywSlUP+tJW4GoYlbHW93w3LoCVt2whq0qV7RjfsW4rdazWuF/QS4FbcbWU9SIyUUSOIQbR8orIz0Tk395FGNuB/+Hwz2id7/meMOtH+Na3qOquCOfnF/FcvaVQVbXUcSLZRPT3G+AtoIWI9MLVsDJwge8wZbzXrXG12NKOCVPG0n93/s89GxdA1/jO/1lcDcZEYMGlenkJV2O5EnhPVf1fPK8Ak3Ft0o2B0bimhHB24f7hQ5r7nq8CXlbVJr6lgaqOCnOcH4HWpTpM2+DatGNR3im9y1O2kNalyvaj71gjSx0rw/sVjKq+oqqn4r6YFHgk1jJHyfsM7hd2O1VthGtOjPQZxeJIEWkQ4fz8op3rGqBlqYtF2kR5zfeBX0XrJFfV3cCbuL/Vq4CJqvpTlP0jvV+rcH1Opf3o7etX+u/O/zmtwtXUmvnOv5GqdohUJmPBpbp5CTgLGMLhzQwNgc2quldEegD/HeU4s4HLRaS2iOTh2tlDxgMXiMg5IlJTROqJSF8RaRXmOF/jahZ3eMfqi2uamBjj+awDcspxNU95yhbyOxFp5V3lNBzXYQ2uD+sGr8Yn3mW054tIQxFpLyJnikhd3EUTe4BQ7SxqmcvI2xDXMb9TRE4AbozxvKN5QETqiMhpuE77cOOJIp4r7gKDIuBm7zO8CFcrjuRvuD6hcSKSDSAiLUXkbyLS2bffOODXwMVEuUqsjPfrn8BDItLOK3dnEckEpgA/E5H/FpFaIvJr3EUD/w73Gqq6BndhyF9FpJGI1BCR40SkIs3G1YYFl2rEa6f/AtcpObnU5t8CD4rIDuA+XF9FJH/C/SLcgruqq7h5TVVXAQNwv6o34H71DSPM35r3a/QC4Dxck93TwNWquijGUwp9EW4SkVll7Vyesvm8gvtiWYZrYnnYO9YMXJB+Evc+LAWu8fLUBUZ557QW13xyd4xljpb3dlzQ34H7wn8tTP7yWOuV/UdgAnBDuPc+2rl6n+FF3vpmXEB4K9ILen1XJ+M6/b/2/t4+wF21tdS36yde2mpVjdaHE+39+hvu73gaLig/D9T3+l1+CdyGa6a7A/ilqm6M8jpX4y5eCF05+CZlN+9Va1KyqdQYUx14tcTxqhqt1mZMhVnNxRhjTNwFFlxE5CER+U5EZovINN8VMSIiT4jIUm97N1+eQSKyxFsG+dK7i8hcL88TpToXjTHGJFlgzWIi0khVt3vPbwZOVNUbROQXwO9x15X3BP6hqj29DtUZQB7uSo6ZQHdV3SIi3wA34zqIpwBPqOq7yT8rY4wxEGDNJRRYPA04dOnfAOAlb9DTV0ATEWkBnANMV9XNqroFN4r3XG9bI29wmeKuiLoweWdijDGmtEBnwxWRkbirMLYBZ3jJLSk5gGm1lxYtfXWY9HCvNxQ32pgGDRp0P+GEEyp/EsYYU43MnDlzo6pmlbVfQoOLiLxPyQF2IcNV9R1VHQ4MF5G7gZuA+xNZHlUdA4wByMvL0xkzbAZvY4wpDxGJNgNDsYQGF1WN9UZLE3B9JffjRsn6R0W38tIKcVNB+NM/8tJbhdnfGGNMQIK8Wqydb3UAbloLcIP7rvauGusFbPNGyL4H9BeRI0XkSKA/bgqTNcB2EenlXSV2NW5mWGOMMQEJss9llIi0x03VsAI3USK4GswvcKN1dwPXghvZKyIPcWjG1Qe90b7gRpePxU2x/q63GGOMCUi1HaEfrs9l//79rF69mr179wZUKlPV1atXj1atWlG7du2gi2JMQojITFXNK2u/VL13eiBWr15Nw4YNycnJwcZhmvJSVTZt2sTq1atp27Zt0MUxJlA2/YvP3r17yczMtMBiKkREyMzMtJqvMVhwOYwFFlMZ9vdjjGPBxRhjTNxZcEkxNWvWpEuXLnTs2JELLriArVu3xuW4BQUFdOzYMS7HCsqIESN47LHHgi6GMSYGFlwqY8IEyMmBGjXc44QJlT5k/fr1mT17NvPmzaNp06Y89dRTlT5mVaKqHDx4sOwdjTEpzYJLRU2YAEOHwooVoOoehw6NS4AJ6d27N4WFbrKBnTt30q9fP7p160anTp145x03TrSgoICf//znDBkyhA4dOtC/f3/27NkDwMyZM8nNzSU3N7dEkNq7dy/XXnstnTp1omvXrnz44YcAjB07lgsvvJCzzz6bnJwcnnzySf72t7/RtWtXevXqxebNmyntjTfeoGPHjuTm5tKnTx8ADhw4wLBhwzjppJPo3Lkzzz77bJnn0L59e66++mo6duzIqlWrmDp1Kt26dSM3N5d+/foVv96CBQvo27cvxx57LE888UTc3mtjTJyparVcunfvrqUtWLDg0Mott6iefnrkpW5dVRdWSi5160bOc8sth71maQ0aNFBV1aKiIr3kkkv03XffVVXV/fv367Zt21RVdcOGDXrcccfpwYMHdfny5VqzZk399ttvVVX10ksv1ZdffllVVTt16qQff/yxqqrefvvt2qFDB1VVfeyxx/Taa69VVdWFCxdq69atdc+ePfriiy/qcccdp9u3b9f169dro0aN9JlnnlFV1VtvvVUff/zxw8rbsWNHXb16taqqbtmyRVVVn332WX3ooYdUVXXv3r3avXt3XbZsWdRzEBH98ssvVVV1/fr12qpVK122bJmqqm7atElVVe+//37t3bu37t27Vzds2KBNmzbVn376qcz3NNlK/B0Zk2aAGRrDd6zVXCpq377ypcdoz549dOnShebNm7Nu3TrOPvtswP0IuOeee+jcuTNnnXUWhYWFrFu3DoC2bdvSpUsXALp3705BQQFbt25l69atxbWJq666qvg1PvvsM6688koATjjhBLKzs/n+++8BOOOMM2jYsCFZWVk0btyYCy64AIBOnTpRUFBwWHlPOeUUrrnmGp577jkOHDgAwLRp03jppZfo0qULPXv2ZNOmTSxZsiTqOWRnZ9OrVy8AvvrqK/r06VM8VqRp06bFr3f++edTt25dmjVrxlFHHVWc3xiTWmwQZSR//3v07Tk5rimstOxs+OijCr9sqM9l9+7dnHPOOTz11FPcfPPNTJgwgQ0bNjBz5kxq165NTk5O8XiKunXrFuevWbNmcbNYRfiPVaNGjeL1GjVqUFRUdNj+o0eP5uuvv+Y///kP3bt3Z+bMmagq//u//8s555xTYt+xY8dGPIcGDRqUu3w1a9YMWyZjTPCs5lJRI0dCRkbJtIwMlx4HGRkZPPHEE/z1r3+lqKiIbdu2cdRRR1G7dm0+/PBDVoQLbD5NmjShSZMmfPbZZwBM8PUFnXbaacXr33//PStXrqR9+/YVKucPP/xAz549efDBB8nKymLVqlWcc845PPPMM+zfv7/4NXbt2hXzOfTq1YtPPvmE5cuXA4Tt6zHGpDaruVTUwIHucfhwWLkS2rRxgSWUHgddu3alc+fOvPrqqwwcOJALLriATp06kZeXRyw3OnvxxRe57rrrEBH69+9fnP7b3/6WG2+8kU6dOlGrVi3Gjh1bokZQHsOGDStu8urXrx+5ubl07tyZgoICunXrhqqSlZXF22+/HfM5ZGVlMWbMGC666CIOHjzIUUcdxfTp0ytUPmNMQGLpmEnHpcwOfWMqyP6O0sv48arZ2aoi7nH8+Pjun6w8FXmNcIixQ99qLsYYE0FoxMHu3W59xQoYPBiWLIFSXYoAvPcejBp16LqesvZPVp5w+w8d6p7HsbGlBJty32fhwoX8/Oc/D6hEJl3Y31H6iHTdTrrIzoYwF4FGZVPuG2NMJa1cGT5dBN4Nc0vC885zA95i3T9ZeSLtH+n84sGCizHGRNC8OaxZc3h6mzbhm5/atAlf04m0f7LyRNs/UexSZGOMiaB168PToo04qMgIhWTkSfDIifBi6fWP9wI8BHwHzAamAcd46QO99LnAF0CuL0+Blz4b39UKQFNgOrDEezwyljLY1WImUezvKD3MnasKqv/1X3a1mB8xXi0WVHBp5Ht+MzDae35yKDgA5wFf+/YrAJqFOdZfgLu853cBj8RShlQNLjVq1NDc3Fzt3Lmzdu3aVT///POkvO7gwYN1/vz5SXktvy1btuhTTz1VvF5YWKgXX3xxuY7xpz/9SadPn17u1540aVKJc67ocUpLhb8jU3mXXKLasKGqN7Wd8aR0cClRALgbeCZM+pFAoW89UnBZDLTwnrcAFsfyuvEILvH6JeAXmrhSVXXq1Knap0+fyh80hS1fvrx4Qs1kGzRokL7xxhtxP64Fl6pvzhz37XjvvUGXJPXEGlwC63MRkZEisgrXFHZfmF0GA/7rHhSYJiIzRWSoL/1oVQ11ua0Fjk5IgUtJwoz7bN++nSOPPBKIPF39fffdx99986ANHz6cf/zjHwA8+uijxdPe33///QDs2rWL888/n9zcXDp27Mhrr70GQN++fQldmn3jjTeSl5dHhw4divMB5OTkcP/99xeXYdGiRYeVOdp0/gMGDKBv3760a9eOBx54AIC77rqLH374gS5dujBs2LASNzWL9RYA11xzDW+++SYzZsygS5cudOnShU6dOhXfcvi5557jpJNOIjc3l4svvpjdu3fzxRdfMHnyZIYNG0aXLl344Ycfio8D8MEHH9C1a1c6derEddddxz5vgEAs74Gp+h54ABo1gj/+MeiSVGGxRKCKLMD7wLwwy4BS+90NPFAq7QxgIZDpS2vpPR4FzAH6eOtbS+XdEqVMQ4EZwIw2bdocFpH9vzgDmnG/uFmsffv22qhRI50xY4aqRp9yv2vXrqqqeuDAAT322GN148aN+t577+mQIUP04MGDeuDAAT3//PP1448/1jfffFOvv/764tfbunWrqqqefvrpmp+fr6qHprgvKirS008/XefMmaOqqtnZ2frEE0+oqupTTz2lgwcPPqz80abzb968uW7cuFF3796tHTp00Pz8/MNqLv71WG8BEK4Gcvvtt+vtt9+uqqobN24sTh8+fHjxOZTOF1rfs2ePtmrVShcvXqyqqldddVXxa8XyHljNpWr79lv3v3zffUGXJDURdM1FVc9S1Y5hlndK7ToBuDi0IiKdgX/igtAm3/EKvcf1wCSgh7dpnYi08PK2ANZHKdMYVc1T1bysrKxKnV+CZtwvnhV50aJFTJ06lauvvrr4wwo3XX1OTg6ZmZl8++23TJs2ja5du5KZmcm0adOK17t168aiRYtYsmQJnTp1Yvr06dx55518+umnNG7c+LAyvP7663Tr1o2uXbsyf/58FixYULztoosuAg5N7V9atOn8zz77bDIzM6lfvz4XXXRR8aSa0ZT3FgAAr732GrNmzWLUqFEAzJs3j9NOO41OnToxYcIE5s+fH/U1Fy9eTNu2bfnZz34GwKBBg/jkk09ifg9M1fbAA9C4MfzhD0GXpGoLZJyLiLRT1SXe6gBgkZfeBngLuEpVv/ft3wCooao7vOf9gQe9zZOBQcAo77F08KqQgGbcL6F3795s3LiRDRs2MGXKlIjT1V9//fWMHTuWtWvXct111wGuRnr33Xfzm9/85rDjzpo1iylTpnDvvffSr18/7rvvUKvk8uXLeeyxx8jPz+fII4/kmmuuKX4dODTlfUWmuw81U0VaD6e8twCYN28eI0aM4JNPPqFmzZqAazZ7++23yc3NZezYsXxUyQ+oMu+BSW3ffgtvvw0jRkCTJkGXpmoLqs9llIjME5HvcIHiFi/9PiATeFpEZotIaH6Wo4HPRGQO8A3wH1WdGjoWcLaILAHO8tYTLhnXjS9atIgDBw6QmZkZdbr6X/3qV0ydOpX8/Pzie6icc845vPDCC+zcuROAwsJC1q9fz48//khGRgZXXnklw4YNY9asWSVec/v27TRo0IDGjRuzbt063o00RDiCaNP5T58+nc2bN7Nnzx7efvttTjnlFBo2bMiOHTsq/B75bd26lSuuuIKXXnoJf810x44dtGjRgv3795e49UCk127fvj0FBQUsXboUgJdffpnTTz89LmU0qS0UVG69NeiSVH2B1FxU9eII6dcD14dJXwbkRsizCegXblsiJWrG/dCdKMHVPsaNG0fNmjWjTldfp04dzjjjDJo0aVL8a71///4sXLiQ3r17A3DEEUcwfvx4li5dyrBhw6hRowa1a9fmmWeeKfH6ubm5dO3alRNOOIHWrVtzyimnlKv80abz79GjBxdffDGrV6/myiuvJC/PTU90yimn0LFjR8477zx+97vfVeyNA9555x1WrFjBkCFDitNmz57NQw89RM+ePcnKyqJnz57FAeXyyy9nyJAhPPHEE8Ud+QD16tXjxRdf5NJLL6WoqIiTTjqJG264ocLlMlXDzJkweTI8+KBrFjOVYxNX+lTVCQcPHjxIt27deOONN2jXrl3QxQlr7NixzJgxgyeffDLooiRcVf07qu4uuAA+/9xN5NioUdClSV2xTlxp079UcQsWLOD444+nX79+KRtYjEl1+fnw73/DbbdZYIkXq7n42C9OEw/2d1T1nH8+fPUVLF9uwaUsVnOpoOoabE182N9P1fP11zBlitVa4s2Ci0+9evXYtGmTfUGYClFVNm3aRL169YIuiimHESMgMxN+//ugS5Je7H4uPq1atWL16tVs2LAh6KKYKqpevXq0atUq6GKYGH31FUydCn/+MzRsGHRp0osFF5/atWvTtm3boIthjEmSESOgWTO46aagS5J+rFnMGFMtffklvPceDBsGRxwRdGnSjwUXY0y1dP/9kJUFlRi3a6KwZjFjTLXz+ecwfTo8+ig0aBB0adKT1VxMlTZhgptEtEYN9xjL/XRSNY+VK3nlOvVUl69p07LzmAqKZV7+dFzC3YnSVC3jx6tmZJS8n079+qrPP6+6c2f45fnn3T6plsfKFUy5MjLicwfZ6oQY7+diI/RNlRXptgfGlEd2tptPzMQm1hH61udiqiTV6IHlL38Jn37HHamZx8oVXLlWrox8LFMJsVRv0nGxZrGq67vvVE87rWTzhn/Jzo6cNzs7NfNYuVKzXOZwBH2bY2Pibft2+OMfoWtXWLAABg8u/w3bKnKTt2TksXKlZrlMJcQSgdJxsZpL1XHwoOorr6i2aKEqojp0qOrGjW7b+PHul6eIe4ylczZV81i5UrNcpiRirLkE/iUf1GLBpXyC+oJ55BHVM85wf6ndu6t+/XVlzsIYU1mxBhfr0DdlmjABhg6F3bvd+ooVbh0i39Y5XnnuvNM1XTzzDAwZAt5dnI0xKS6Q4CIiDwEDgIPAeuAaVf1RRPoC7wDLvV3fUtUHvTznAv8AagL/VNVRXnpbYCKQCcwErlLVn5J4Omlv+PBDX/ghu3fDzTfDnj3h89x5Z3zygBvoZrewN6ZqCWSci4g0UtXt3vObgRNV9QYvuNyuqr8stX9N4HvgbGA1kA9coaoLROR1XBCaKCKjgTmq+kxZZbBxLrGrUcNdVxMUETh4MLjXN8YcktJ3ogwFFk8DoKyvrh7AUlVd5tVKJgIDRESAM4E3vf3GARfGu7zVXZs24dNbtoRVq8IvLVvGL0+k1zfGpK7ALkUWkZEisgoYCNzn29RbROaIyLsi0sFLawms8u2z2kvLBLaqalGp9EivOVREZojIDLshWOwiXcL5yCPQqlX45ZFH4pfHLhU1pupJWHARkfdFZF6YZQCAqg5X1dbABCB0q55ZQLaq5gL/C7wdzzKp6hhVzVPVvKysrHgeOq0NHAijR7vmKXDTZYwZE7ljPpRnzBi3r0ji8hhjUlPCOvRV9awYd50ATAHu9zeXqeoUEXlaRJoBhUBrX55WXtomoImI1PJqL6F0E2e5ua7fZfz42L/sBw4sf2CoSB5jTOoJpFlMRNr5VgcAi7z05l4/CiLSA1e+TbgO/HYi0lZE6gCXA5O9a64/BC7xjjUId7WZibP8fPd40knBlsMYUzUENc5llIi0x12KvAIIXWh6CXCjiBQBe4DLvQBSJCI3Ae/hLkV+QVXne3nuBCaKyMPAt8DzSTyPaiM/Hxo3huOPD7okxpiqwKbcNzHp1g0yM93d+4wx1VdKX4psqpa9e2HuXGsSM8bEzoKLKdPs2VBUZMHFGBM7Cy6mTKHO/B49gi2HMabqsOBiyvTNN9CiReQR9MYYU5oFF1Om/HxrEjPGlI8FFxPVtm2weLEFF2NM+VhwMVGFrta2/hZjTHlYcDFRhTrz88q8qt0YYw6x4GKiys+H445zN+wyxphYWXAxUeXnW5OYMab8LLiYiNaudTfxss78JJkwAXJy3K0/c3LceirksXJV33JVhqpWy6V79+5qops8WRVUP/006JJUA+PHq2ZkuDc8tGRkuPQg81i5qm+5IgBmaAzfsTZxpYnovvvgf/7HXY7coEHQpUlzOTmwYsXh6UccEfkGNxMmwM6dic2TjNewcgVXruxsKCgI/xoRxDpxpQUXE9G558KaNTBnTtAlqQZq1HC/J8M5+ujw6evWRT5evPIk4zWsXMGVSwQOHox8rLBZYgsugTdPBbVYs1h0Bw+qNm2qOnhw0CWpJrKzSzZZhJbs7GDzWLmqb7kiIMZmMevQN2EtXw6bN1tnftKMHAm1St27LyPDpUfLk5GR2DzJeA0rV2qWq7JiiUDpuFjNJbqJE90Pm1mzgi5JNbF3r2qDBqr166uKuF+UsXS2jh/v9k1knmS8hpUrNcsVBtahH531uUR3223w9NOwfTvUrh10aaqBV15xHbHTpsHZZwddGmMiSuk7UYrIQyLynYjMFpFpInKMlz7MS5stIvNE5ICINPW2FYjIXG/bDN+xmorIdBFZ4j0eGcQ5pZv8fOjSxQJL0owe7aZC6Ncv6JIYExdB9bk8qqqdVbUL8G/gPgBVfVRVu3jpdwMfq+pmX74zvO3+qHkX8IGqtgM+8NZNJRQVwcyZNjI/aebPh08/hd/8xl01ZkwaCOQvWVW3+1YbAOHa5q4AXo3hcAOAcd7zccCFlSudWbgQdu+2zvykefZZqFMHrrkm6JIYEzeB/UwSkZEisgoYiFdz8W3LAM4F/uVLVmCaiMwUkaG+9KNVdY33fC0Q4cJwEJGhIjJDRGZs2LAhLueRjkIzIVtwSYJdu+Cll+CSSyArK+jSGBM3CQsuIvK+129SehkAoKrDVbU1MAG4qVT2C4DPSzWJnaqq3YDzgN+JSJ/Sr+ldyRDxCgVVHaOqeaqal2X/yBHl50OjRtCuXdAlqQZee81NgXDDDUGXxJi4qlX2LhWjqmfFuOsEYApwvy/tcko1ialqofe4XkQmAT2AT4B1ItJCVdeISAtgfaULX819842rtVjzfxKMHg0nnginnhp0SYyJq6CuFvP/Jh4ALPJtawycDrzjS2sgIg1Dz4H+wDxv82RgkPd8kD97DOJmAAAae0lEQVSfKb+9e+G776xJLClmznTVxBtucNNwGJNGElZzKcMoEWkPHARWAP42gV8B01R1ly/taGCSuH/AWsArqjo1dCzgdREZ7B3rskQXPp3NmeOuFrPgkgTPPgv168NVVwVdEmPiLpDgoqoXR9k2FhhbKm0ZkBth/02ADQ6Ik1Bnvl2GnGDbtrmBk1dcAU2aBF0aY+IuYrOYiLzue/5IqW3TElkoE5xvvoHmzaFly6BLkuYmTHBXillHvklT0fpc/P0ipeejsEut0lR+vmsSsy6ABFJ1HfndukFe2TOXG1MVRQsu0SYdq54TkqW5bdtg8WLrb0m4L7+EuXOtI9+ktWh9Lhki0hUXgOp7z8Vb6iejcCa5Zs50P6qtvyXBRo+Ghg1df4sxaSpacFkL/C3M89C6STOhznxrqUmgTZvg9ddh8GB3S1pj0lTE4KKqfZNYDpMC8vPh2GMhMzPokqSxceNg3z43SaUxaSza1WIniUhz3/rVIvKOiDwRmgbfpJf8fGsSS6hQR/7JJ0PnzkGXxpiEitah/yzwE4A3j9co4CVgGzAm8UUzybRuHaxcaZ35CfXhh7BkiV1+bKqFaH0uNX0TR/4aGKOq/wL+JSKzE180k0w2E3ISjB4NTZu6GZCNSXPRai41RSQUfPoB/8+3LahpY0yC5Oe7iSq7dQu6JGlq7VqYNMnds6W+XWxp0l+0IPEq8LGIbAT2AJ8CiMjxuKYxk0a++QY6dIAGDYIuSZp64QU3advQoWXva0waiHa12EgR+QBogZtIMjRwsgbw+2QUziSHqqu5DBgQdEnS1IEDMGYMnHkmtG8fdGmMSYqIwcW7Iux7b6krInW9TRu9xaSJggI3/ML6WxLkvfdgxQp49NGgS2JM0kRrFtsIrAaKvHX/PBUKHJuoQpnkspmQE2z0aDj6aKsammolWof+E8AWYCruJlzHqmpbb7HAkka++Qbq1oVOnYIuSQVMmAA5Oe5qhJwct55KeVq1gv/7P9izB954o+w8xqQLVY244GorZ+DGtcwG/gK0jZanqizdu3dX4/Tpo9qzZ9ClqIDx41UzMlRdt5FbMjJcelXMY0wVAMzQGL5jo15S7B3oQxH5Fndf+4eAJcBzCYx3JokOHHATVl53XdAlqYDhw2H37pJpu3fDLbfATz+FzzNsWLB5hg+HgQPD5zEmjYhq+NnzvXvVD8ANoMwC3gJeV9WVySte4uTl5emMGTOCLkbg5s1zzWEvvVQF77Zbo4arE1QlInDwYNClMKbCRGSmqpY5vW20mst6XC1loveoQJ6I5AGo6ltxKuhtwGNAlqpuFBEB/gH8AtgNXKOqs7x9BwH3elkfVtVxXnp33K2R6wNTgFs0UtQ0JVTpkflHH+0GJ5bWsiV8/nn4PKecAoWFweVp0yb8/sakmWjB5Q1cQGnvLX6Kq8lUioi0BvoD/trQebi7YLYDegLPAD29S6PvB/K8158pIpNVdYu3zxDga1xwORd4t7Llqw7y86FRI/jZz4IuSTm9/DJs2OBqAv7fERkZ8MgjkJ0dPt8jj7iBjP4mq2TmGTkytvMzpqqLpWMmUQvwJpALFADNvLRngSt8+yzGDeS8AnjWl/6sl9YCWORLL7FfpMU69J3u3VXPPDPoUpTD/v2qf/iD6yA/4wzVZ55Rzc5WFXGPsXSYjx+funmMSXHEo0M/kURkAFCoqnOk5K1eWwKrfOurvbRo6avDpId7zaHAUIA21jzBvn3w3Xfwxz8GXZIYbd4Mv/41vP8+3HwzPPYY1K5d/lmGBw4sf6d6svIYkyYSGlxE5H2geZhNw4F7cE1iSaOqY/BuF5CXl1ft+2TmzIH9+6tIf8vcuXDhhbB6tZun69prgy6RMSaKaIMoK01Vz1LVjqUXYBnQFpgjIgVAK2CWd3OyQqC17zCtvLRo6a3CpFdJyRzfd+657vktt8SWJzBvvQW9e7uBiB9/bIHFmKoglraz0gvQvCL5ohyvgEN9LufjOuMF6AV846U3BZYDR3rLcqCpt+0bb1/x8v6irNdMxT4XG99XyoEDqn/6kytgr16qhYVBl8iYao8E97k87wWBRJiCuwx5Ke5S5GsBVHWziDwEeBfP8qAeupnZbzl0KfK7VNErxSKNCbzpJtcaFM6oUfHLE3V834QJboeVK93ltCNHlt2fUNk89eq52sp118HTT7s5aowxVULEQZTpLhUHUQY9JlBQDq5YdfiGt9+Gu+5yX/Qh9eu7KHXhheEPFq88tWvDiy9ax7gxKSLWQZRlBhdvfElpO1R1f0ULlwpSMbjk5LiZ2Utr3RoWLw6fp317WBUmHkTN07CQVQcOv6AumwIKaBt7gZMlO9vdF8AYE7h4jNAPmYXrSN+C69NoAqwVkXXAEFWdWamSmmIjR4Yfd/fnP0e+M+6f/1yBPAfuYChj2M2h205msIuR3APPP394hsGDIxc63P7xzrMyLWYcMqZ6KatTBjdJ5Tm+9f64AYy9gK9j6dhJxSUVO/RVXad6/fquDzshY/UOHlTNyNDxXKHZLFfhgGazXMdzhcscTnZ2yd7/0BJp/2TmMcYkFTF26McSXOaGSfvOe5wdy4uk4pKqwUXVjZo/99wEHfyRR9zHXrt2yS/waJeL2WVsxhhPrMEllnEua0TkThHJ9pY7gHUiUhOw6V0ToLDQzYkYd9Onw913w2WXuU7y7Gw3N1d2trvHe6RO84ED3fZY909mHmNMSoqlQ78ZbsLIU3ETRn4OPAhsA9qo6tJEFzIRUrFDH9yI+bp14U9/ggceiOOBCwogLw9atIAvv4QjjojjwY0x1UXcOvRVdSPwexFpoKq7Sm2ukoElla1d69qD4lpz2bMHLroIiopg0iQLLMaYhCuzWUxEThaRBcBCbz1XRJ5OeMmqqdAtQOIWXFTdxI6zZ7sBiscfH6cDG2NMZLH0uTwOnANsAlDVOUCfRBaqOot7cHnqKXebyREj4PxETapgjDElxTRxpaqWHqZ3IAFlMcQ5uHz6KfzhD3DBBXDvvWXvb4wxcRLLIMpVInIyoCJSG7gFr4nMxF9hIdSpA82axeFAl14Kbdu6uzbWSOgE2MYYU0IsweUG3D3tW+Kmsp8G/C6RharOCgvhmGPclbgVtm8fXHIJ7NwJH3wAjRvHrXzGGBOLWK8Ws4EGSRKXMS633gpffQVvvAEdOsSlXMYYUx4Rg4uI3Bcln6rqQwkoT7VXWAhdu1biAC+8AKNHw513utqLMcYEIFpD/K4wC8Bg4M4El6taUoXClUW0fPefFb8V5eDBrrYycmSii2uMMRFFrLmo6l9Dz0WkIa4j/1pgIvDXSPlMxW177nV277uMlvsWAurm3x8yBDZvhl/9KnymSZNcLcV/D5Rly2DiRJs2xRgTmKjTv3j3cvkjrs9lHPAPVd2SpLIlVCpO/zL/mLPpuGY6r3I5l/Na5Q5m90AxxiRApad/EZFHgYuAMUAnVd0Zx/KZMArXuFbKlhQevvG558JnGjIkfLrdA8UYE6BoV4vdBuwD7gWGy6FrYwXXod+osi8uIrcBjwFZqrpRRAbi+nME2AHc6M0IgIgUeGkHgKJQ5PRqV68BOUABcFlVrV0VZnaGTWGCS3Y2XH99+EwPPxz+9pVt2sS/gMYYE6OIHfqqWkNV66tqQ1Vt5FsaximwtMbdeMz/E3s5cLqqdgIewtWa/M5Q1S6lqmR3AR+oajvgA2+9Sio840oAjuHHQ4kZGdE750eOdPv4lZXHGGMSLMhh248Dd+Cm8QdAVb/w1Tq+AlrFcJwBuP4gvMcL41nIZCpslkvmEXupV9/7WOweKMaYKiqWEfpxJyIDgEJVnSORh6IPBt71rSswTUQUeFZVQ7Wao1V1jfd8LXB0lNcdCgwFaJOCzUaFhdDy2HrQoIurfbz/fmwZBw60YGKMSSkJCy4i8j7QPMym4cA9uCaxSHnPwAWXU33Jp6pqoYgcBUwXkUWq+ok/n6qqF3zC8gLSGHBXi8V8MklSPDr/+/XQo0fQxTHGmApLWHBR1bPCpYtIJ6AtEKq1tAJmiUgPVV0rIp2BfwLnqeom3/EKvcf1IjIJ6AF8grvlcgtVXSMiLYD1iTqnRCsshG7dgM/Ww9ERK2DGGJPykt7noqpzVfUoVc1R1RxgNdDNCyxtgLeAq1T1+1AeEWngDeRERBrgaj3zvM2TgUHe80HAO0k6lbjavx/Wr4eWR+2HHTvgqKOCLpIxxlRYIH0uUdwHZAJPe7Wa0CXHRwOTvLRawCuqOtXLMwp4XUQGAyuAy5Je6jhYs8a7vXHD7S7BgosxpgoLPLh4tZfQ8+uBwwZ0qOoyIDdC/k1Av0SVL1mKbxJWz2sJtGYxY0wVZneQShHFwaWmd+Gb1VyMMVWYBZcUURxcDq52Tyy4GGOqMAsuKaKwEOrWhczdq1yCBRdjTBVmwSVFFN/eeP06OOKIw6d0McaYKsSCS4ooHkC5fr3VWowxVZ4FlxRRIrjYlWLGmCrOgksKUPUFl3XrrOZijKnyLLikgK1b3V2KrVnMGJMuLLikgOLLkFschA0brFnMGFPlWXBJAcXB5YhtcPCg1VyMMVWeBZcUUBxc6mxwTyy4GGOqOAsuKWC1Nyi/+PbG1ixmjKniLLikgMJCaNYM6m5Z6xKs5mKMqeIsuKSAEmNcwIKLMabKs+CSAkoEl5o1oWnToItkjDGVYsElBZQYQJmVBTXsYzHGVG32LRawffvc0BYbQGmMSScWXAK2xrs3mAUXY0w6CTS4iMhtIqIi0sxb7ysi20Rktrfc59v3XBFZLCJLReQuX3pbEfnaS39NROoEcS4VVTzGJdQsZpchG2PSQGDBRURaA/2BlaU2faqqXbzlQW/fmsBTwHnAicAVInKit/8jwOOqejywBRiclBOIkxLBxWouxpg0EWTN5XHgDkBj2LcHsFRVl6nqT8BEYICICHAm8Ka33zjgwkQUNlGKg0uTXbBrlwUXY0xaCCS4iMgAoFBV54TZ3FtE5ojIuyLSwUtrCazy7bPaS8sEtqpqUan0SK87VERmiMiMDRs2VP5E4iB0e+OmRd4YF2sWM8akgVqJOrCIvA80D7NpOHAPrkmstFlAtqruFJFfAG8D7eJVJlUdA4wByMvLi6XGlHChy5Blgw2gNMakj4QFF1U9K1y6iHQC2gJzXKsWrYBZItJDVdf68k8Rkae9zv5CoLXvMK28tE1AExGp5dVeQulVRmEhtGqFjc43xqSVpDeLqepcVT1KVXNUNQfXlNVNVdeKSHOvHwUR6eGVbxOQD7TzrgyrA1wOTFZVBT4ELvEOPwh4J8mnVCklBlCCNYsZY9JCwmouFXQJcKOIFAF7gMu9AFIkIjcB7wE1gRdUdb6X505goog8DHwLPB9AuSukxO2NQzWXrKxAy2SMMfEQeHDxai+h508CT0bYbwowJUz6MtzVZFXO5s1uhH7LlkDBemjYEOrXD7pYxhhTaTZCP0A2gNIYk64suATIBlAaY9KVBZcAWXAxxqQrCy4BCgWXFi2wZjFjTFqx4BKgwkJXWalT8wBs3Gg1F2NM2rDgEqDiy5A3bXLXJVtwMcakCQsuAbIBlMaYdGXBJUCHDaC0mosxJk1YcAnIvn2um8WCizEmHVlwCciPP7pHaxYzxqQjCy4BOWyMS61a0KRJoGUyxph4seASkMOCS1YW1LCPwxiTHuzbLCA2r5gxJp1ZcAlIYaGbALlJE2zqF2NM2rHgEpDi2xsLFlyMMWnHgktAise4qFqzmDEm7VhwCUhxcNm1C/bssZqLMSatWHAJgKob52IDKI0x6SrQ4CIit4mIikgzb32YiMz2lnkickBEmnrbCkRkrrdthu8YTUVkuogs8R6PDOp8YrVpk+/2xjaA0hiThgILLiLSGugPrAylqeqjqtpFVbsAdwMfq+pmX7YzvO15vrS7gA9UtR3wgbee0g4b4wJWczHGpJUgay6PA3cAGmH7FcCrMRxnADDOez4OuLDyRUssCy7GmHQXSHARkQFAoarOibA9AzgX+JcvWYFpIjJTRIb60o9W1TXe87VAyrcvHTaAEtwIfWOMSRO1EnVgEXkfaB5m03DgHlyTWCQXAJ+XahI7VVULReQoYLqILFLVT/yZVFVFJFJNCC8oDQVo06ZNjGcSf4WFbnxLixa4mkvjxlCvXmDlMcaYeEtYcFHVs8Kli0gnoC0wR0QAWgGzRKSHqq71drucUk1iqlroPa4XkUlAD+ATYJ2ItFDVNSLSAlgfpUxjgDEAeXl5EYNQooVub1y7NjaA0hiTlpLeLKaqc1X1KFXNUdUcYDXQLRRYRKQxcDrwTiiPiDQQkYah57hazzxv82RgkPd8kD9fqioe4wKuWcyCizEmzSSs5lIJvwKmqeouX9rRwCSvplMLeEVVp3rbRgGvi8hgYAVwWTILWxGFhZCd7a2sXw8nnBBoeYwxJt4CDy5e7cW/PhYYWyptGZAbIf8moF9iSpcYhYVw8sneyvr10KdPoOUxxph4sxH6SbZ3rxtE2bIlUFTkVqxZzBiTZiy4JFmJ2xtv3OjmgrHR+caYNGPBJclsAKUxpjqw4JJkYQdQWnAxxqQZCy5JFrbmYs1ixpg0Y8ElyQoLISPDDcq3ZjFjTLqy4JJkJW5vvG6dG6bfpEnQxTLGmLiy4JJkJUbnh6Z+cYNDjTEmbVhwSbKwwcUYY9KMBZckKnF7Y7B5xYwxacuCSxJt3Ag//VSq5mJXihlj0pAFlyQqcRmyqjWLGWPSlgWXJCoRXHbscBONWXAxxqQhCy5JZAMojTHVhQWXJArd3rh5c2wApTEmrVlwSaLCQldRqV0bm1fMGJPWLLgk0WFjXMCaxYwxacmCSxKFDS5ZWYGVxxhjEsWCSxKVCC7r1rk5xerUCbRMxhiTCIEEFxEZISKFIjLbW37h23a3iCwVkcUico4v/VwvbamI3OVLbysiX3vpr4lISn5b79kDmzfbAEpjTPUQZM3lcVXt4i1TAETkROByoANwLvC0iNQUkZrAU8B5wInAFd6+AI94xzoe2AIMTvaJxKLE7Y3BBlAaY9JaqjWLDQAmquo+VV0OLAV6eMtSVV2mqj8BE4EBIiLAmcCbXv5xwIUBlLtMJca4gAUXY0xaqxXga98kIlcDM4DbVHUL0BL4yrfPai8NYFWp9J5AJrBVVYvC7H8YERkKDPVWd4rI4gqWvRmwsSIZ+/f3rSxcWBWn26/wuaeJ6nz+1fncoXqfv//cs2PJkLDgIiLvA83DbBoOPAM8BKj3+FfgukSVJURVxwBjKnscEZmhqnlxKFKVU53PHar3+Vfnc4fqff4VOfeEBRdVPSuW/UTkOeDf3moh0Nq3uZWXRoT0TUATEanl1V78+xtjjAlIUFeLtfCt/gqY5z2fDFwuInVFpC3QDvgGyAfaeVeG1cF1+k9WVQU+BC7x8g8C3knGORhjjIksqD6Xv4hIF1yzWAHwGwBVnS8irwMLgCLgd6p6AEBEbgLeA2oCL6jqfO9YdwITReRh4Fvg+SSUv9JNa1VYdT53qN7nX53PHar3+Zf73MX9+DfGGGPiJ9UuRTbGGJMGLLgYY4yJOwsu5RRpGprqQEQKRGSuN2XPjKDLk2gi8oKIrBeReb60piIyXUSWeI9HBlnGRIlw7hGnbUonItJaRD4UkQUiMl9EbvHS0/6zj3Lu5f7src+lHLxpaL4HzsYN2MwHrlDVBYEWLElEpADIU9VqMZBMRPoAO4GXVLWjl/YXYLOqjvJ+XBypqncGWc5EiHDuI4CdqvpYkGVLNO9q1haqOktEGgIzcTN/XEOaf/ZRzv0yyvnZW82lfMJOQxNwmUyCqOonwOZSyQNw0wxBCk83VFkRzr1aUNU1qjrLe74DWIib+SPtP/so515uFlzKpyWHT0NToTe+ilJgmojM9KbSqY6OVtU13vO1QHWb2vomEfnOazZLu2ah0kQkB+gKfE01++xLnTuU87O34GLK41RV7Yabnfp3XtNJteUN4q1O7crPAMcBXYA1uGmb0paIHAH8C7hVVbf7t6X7Zx/m3Mv92VtwKZ9o09OkPVUt9B7XA5NwzYTVzbrQDBPe4/qAy5M0qrpOVQ+o6kHgOdL48xeR2rgv1wmq+paXXC0++3DnXpHP3oJL+YSdhibgMiWFiDTwOvgQkQZAfw5N21OdTMZNMwTVbLqhKNM2pRXvVh7PAwtV9W++TWn/2Uc694p89na1WDl5l+D9nUPT0IwMuEhJISLH4mor4KYNeiXdz11EXgX64qYbXwfcD7wNvA60AVYAl6lq2nV8Rzj3vrhmkeJpm3x9EGlDRE4FPgXmAge95HtwfQ9p/dlHOfcrKOdnb8HFGGNM3FmzmDHGmLiz4GKMMSbuLLgYY4yJOwsuxhhj4s6CizHGmLiz4GJMJYnITu8xR0T+O87HvqfU+hfxPL4xiWLBxZj4yQHKFVxEpKxbjZcILqp6cjnLZEwgLLgYEz+jgNO8+138QURqisijIpLvTfj3GwAR6Ssin4rIZGCBl/a2NyHo/NCkoCIyCqjvHW+ClxaqJYl37HnePXZ+7Tv2RyLypogsEpEJ3qhrY5KqrF9NxpjY3QXcrqq/BPCCxDZVPUlE6gKfi8g0b99uQEdVXe6tX6eqm0WkPpAvIv9S1btE5CZV7RLmtS7CjZjOxY2izxeRT7xtXYEOwI/A58ApwGfxP11jIrOaizGJ0x+4WkRm46YOyQTaedu+8QUWgJtFZA7wFW5y1HZEdyrwqjeZ4DrgY+Ak37FXe5MMzsY11xmTVFZzMSZxBPi9qr5XIlGkL7Cr1PpZQG9V3S0iHwH1KvG6+3zPD2D/5yYAVnMxJn52AA196+8BN3pTmCMiP/NmlC6tMbDFCywnAL182/aH8pfyKfBrr18nC+gDfBOXszAmDuwXjTHx8x1wwGveGgv8A9ckNcvrVN9A+FvjTgVuEJGFwGJc01jIGOA7EZmlqgN96ZOA3sAc3Ey1d6jqWi84GRM4mxXZGGNM3FmzmDHGmLiz4GKMMSbuLLgYY4yJOwsuxhhj4s6CizHGmLiz4GKMMSbuLLgYY4yJu/8PscUpAU23ygsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x109876828>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "y_rs = np.maximum.accumulate(rs.cv_results_['mean_test_score'])\n",
    "y_bo = np.maximum.accumulate(-optimizer.Y).ravel()\n",
    "\n",
    "print(f'Baseline neg. MSE = {baseline:.2f}')\n",
    "print(f'Random search neg. MSE = {y_rs[-1]:.2f}')\n",
    "print(f'Bayesian optimization neg. MSE = {y_bo[-1]:.2f}')\n",
    "\n",
    "plt.plot(y_rs, 'ro-', label='Random search')\n",
    "plt.plot(y_bo, 'bo-', label='Bayesian optimization')\n",
    "plt.xlabel('Iteration')\n",
    "plt.ylabel('Neg. MSE')\n",
    "plt.ylim(-5000, -3000)\n",
    "plt.title('Value of the best sampled CV score');\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## References\n",
    "\n",
    "\\[1\\] Eric Brochu, Vlad M. Cora, Nando de Freitas, [A Tutorial on Bayesian Optimization of Expensive Cost Functions](https://arxiv.org/abs/1012.2599).  \n",
    "\\[2\\] Jonas Mockus, [Application of Bayesian approach to numerical methods of global and stochastic optimization](https://link.springer.com/article/10.1007/BF01099263).  \n",
    "\\[3\\] Donald R. JonesMatthias SchonlauWilliam J. Welch, [Efficient Global Optimization of Expensive Black-Box Functions](https://link.springer.com/article/10.1023/A:1008306431147).  \n",
    "\\[4\\] Jialei Wang, Scott C. Clark, Eric Liu, Peter I. Frazier, [Parallel Bayesian Global Optimization of Expensive Functions](https://arxiv.org/abs/1602.05149).  "
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
